About: Development and Evaluation of an AI System for COVID-19

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Development and Evaluation of an AI System for COVID-19
Creator	Zhou, Jie Cheng, Jin Zhang, Xin Deng, Lei Shi, Heshui Zheng, Chuansheng Cao, Yukun Chen, Feng, Jianjiang Xu, Zhanwei
Source	MedRxiv
abstract	Early detection of COVID-19 based on chest CT will enable timely treatment of patients and help control the spread of the disease. With rapid spreading of COVID-19 in many countries, however, CT volumes of suspicious patients are increasing at a speed much faster than the availability of human experts. Here, we propose an artificial intelligence (AI) system for fast COVID-19 diagnosis with an accuracy comparable to experienced radiologists. A large dataset was constructed by collecting 970 CT volumes of 496 patients with confirmed COVID-19 and 260 negative cases from three hospitals in Wuhan, China, and 1,125 negative cases from two publicly available chest CT datasets. Trained using only 312 cases, our diagnosis system, which is based on deep convolutional neural network, is able to achieve an accuracy of 94.98%, an area under the receiver operating characteristic curve (AUC) of 97.91%, a sensitivity of 94.06%, and a specificity of 95.47% on an independent external verification dataset of 1,255 cases. In a reader study involving five radiologists, only one radiologist is slightly more accurate than the AI system. The AI system is two orders of magnitude faster than radiologists and the code is available at https://github.com/ChenWWWeixiang/diagnosis_covid19.
has issue date	2020-03-23(xsd:dateTime)
bibo:doi	10.1101/2020.03.20.20039834
has license	medrxiv
sha1sum (hex)	e99f60e5c4287f5ac4dc63e93a60746967ec40cc
schema:url	https://doi.org/10.1101/2020.03.20.20039834
resource representing a document's title	Development and Evaluation of an AI System for COVID-19
resource representing a document's body	covid:e99f60e5c4287f5ac4dc63e93a60746967ec40cc#body_text
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